import matplotlib as mat
import csv
import numpy as np
import matplotlib.pyplot as plt
from math import log10
# import xlrd
# plt.rcParams['font.sans-serif']=['SimHei']
# plt.rcParams['axes.unicode_minus']=False

folder='../../popbin20200529/'
names=['all_Lx39erg_z0.02_rb','all_Lx39erg_z0.02_wind','first_Lx39erg_z0.02_rb','first_Lx39erg_z0.02_wind']
# name='all_Lx39erg_z0.02_rb'
for name in names:
    for num in range(1,20):
        
        seachfile=open("".join([folder,str(num),'/',name,'.out']),'r')
        data_source=csv.reader(seachfile)
        result=seachfile.readlines()
        seachfile.close()
        
        for i in range(len(result)):
            result[i]=result[i].split()
            result[i] = list(map(float, result[i]))
            
        resultnp=np.array(result)
        if(num==1):
            all_result=resultnp
        else:
            all_result=np.append(all_result,resultnp,axis=0)
    np.save(name,all_result)
# xindex=5
# xstep=0.05
# yindex=11

# ystep=0.3
# xlog=True
# ylog=False

# for i in range(len(result)):
#     result[i]=result[i].split()
#     result[i] = list(map(float, result[i]))
    

# # resultnp=np.array(result)
# # np.save("".join([name,'.npy']),resultnp)
# # del result
# # del resultnp

# resultnp=np.load("".join([name,'.npy']))
# result=resultnp.tolist()
# # for i in range(len(result)):
# #     timespan[i]=result[i][7]-result[i][6]
# #     if(xlog):
# #         xdata[i]=log10(result[i][xindex])
# #     else:
# #         xdata[i]=(result[i][xindex])
# #     if(ylog):
# #         ydata[i]=log10(result[i][yindex])
# #     else:
# #         ydata[i]=(result[i][yindex])

# xdata=resultnp[:,xindex]
# ydata=resultnp[:,yindex]
# timespan=resultnp[:,7]-resultnp[:,6]
# if(xlog):
#         xdata=np.log10(xdata)
# if(ylog):
#         ydata=np.log10(ydata)
# x=min(xdata)
# y=min(ydata)
# xrange=[]
# xrangestr=[]
# yrangestr=[]
# yrange=[]
# while (x<max(xdata)):
#     xrange.append(x)
#     xrangestr.append("%.2f" % x)
#     x=x+xstep*xge
# while(y<max(ydata)):
#     yrange.append(y)
#     yrangestr.append("%.2f" % y)
#     y=y+ystep*yge


# datamap=np.zeros((len(xrange)*xge,len(yrange)*yge))
# xnpdata=np.array(xdata)
# ynpdata=np.array(ydata)
# xwei=((xnpdata-min(xdata))/xstep).astype(int)
# ywei=((ynpdata-min(ydata))/ystep).astype(int)
# for i in range(len(xdata)):
#     if(timespan[i]>0.10):continue
#     datamap[xwei[i]][ywei[i]]=datamap[xwei[i]][ywei[i]]+timespan[i]


# # searchxls=xlrd.open_workbook("search20200325beta1,xls")

# datamap=datamap/(np.max(datamap))




# fig, ax = plt.subplots()
# ax.imshow(datamap, interpolation='nearest',origin ='lower')
# plt.xticks(range(1,np.max(ywei),xge),yrangestr)
# plt.yticks(range(1,np.max(xwei),yge),xrangestr)

# # plt.xlabel('campanion mass / Msun')
# # plt.ylabel('orbit period / day')

# plt.xlabel('m1 / Msun')
# plt.ylabel('m2 / Msun')
# plt.title('')
# plt.show()
